A compact reformulation of the two-stage robust resource-constrained project scheduling problem

• Published in: Computers & operations research Vol. 130; p. 105232
• Main Authors: Bold, Matthew, Goerigk, Marc
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.06.2021; Pergamon Press Inc
• Subjects: Algorithms; Budgeted uncertainty; Decision making; Job shops; Operations research; Optimization; Project management; Project scheduling; Resource constraints; Resource scheduling; Robust optimisation; Uncertainty; Resource constraints; Project scheduling; Budgeted uncertainty; Robust optimisation
• ISSN: 0305-0548; 1873-765X; 1873-765X; 0305-0548
• DOI: 10.1016/j.cor.2021.105232

•We consider a two-stage robust resource-constrained project scheduling problem.•Activity durations are uncertain and lie in a budgeted uncertainty set.•A new compact mixed-integer programming formulation for the problem is derived.•In computational experiments we compare against the current best method.•Our approach is easy to apply and solve 49% more instances given the same time. This paper considers the resource-constrained project scheduling problem with uncertain activity durations. We assume that activity durations lie in a budgeted uncertainty set, and follow a robust two-stage approach, where a decision maker must resolve resource conflicts subject to the problem uncertainty, but can determine activity start times after the uncertain activity durations become known. We introduce a new reformulation of the second-stage problem, which enables us to derive a compact robust counterpart to the full two-stage adjustable robust optimisation problem. Computational experiments show that this compact robust counterpart can be solved using standard optimisation software significantly faster than the current state-of-the-art algorithm for solving this problem, reaching optimality for almost 50% more instances on the same benchmark set.